Open Access

Genetic methylation and lymphoid malignancies: biomarkers of tumor progression and targeted therapy

Biomarker Research20131:24

https://doi.org/10.1186/2050-7771-1-24

Received: 3 June 2013

Accepted: 6 August 2013

Published: 14 August 2013

Abstract

Lymphoid malignancies, mainly including lymphocytic leukemia and lymphoma, are a group of heterogeneous diseases. Although the clinical outcome of patients has been significantly improved with current immuno-chemotherapy, definitive biomarkers remain to be investigated, particularly those reflecting the malignant behavior of tumor cells and those helpful for developing optimal targeted therapy. Recently, genome-wide analysis reveals that altered genetic methylations play an important role in tumor progression through regulation of multiple cellular transduction pathways. This review describes the pathogenetic effect of the aberrant genetic methylation in lymphoid malignancies, with special emphasis on potential therapeutic strategies targeting key signaling networks.

Keywords

MethylationLeukemiaLymphomaBiomarkerTargeted therapy

Introduction

Lymphoid malignancies, mainly including lymphocytic leukemia and lymphoma, are a group of disorders that originate from neoplastic transformation of lymphocytes. Diseases vary in cells of origin, histologic appearances, molecular biology, clinical features and disease prognosis. Thus, searching for biomarkers closely related to tumor progression is critical to better understand the disease pathogenesis and to develop subsequent targeted therapy.

DNA methylation plays a pivotal role in transcriptional regulation. Aberrant promoter hypermethylation has been observed in cancer cells, which is responsible for the transcriptional silencing of tumor suppressor genes [1, 2]. For example, tumor suppressor genes, such as p15 (CDKN2B) [3], p16 (CDKN2A) [4], p57 (CDKN1C) [5], p73 (TP73) [6], SHP-1 [7] and DAPK [8], are frequently hypermethylated and related to tumor progression in lymphoid malignancies.

In this review, we described recent advances on alterations of genetic methylation profiling in lymphoid malignancies and highlighted their effects on specific signaling pathways involved in disease progression, which may be helpful in identifying strategies of targeted therapy.

Part I: Genome-wide methylation in lymphoid malignancies

Acute lymphoblastic leukemia (ALL)

Acute lymphoblastic leukemia (ALL) is derived from malignant proliferation of immature lymphoblast cells committed to B- or T-cell lineage. They are the most common, and some of the most curable, tumors in children. ALL has lower prevalence in adults. However, patients usually have much poorer disease outcome.

In T-ALL, methylation pattern of 27 T-ALL-related genes were assessed by methylation specific-polymerase chain reaction (MS-PCR). These genes selected have crucial roles involved in cell cycle arrest (p15, p16, p57 and LATS-2), apoptosis (TMS1, APAF-1, DAPK and DIABLO), differentiation regulation (NES-1), cell adhesion and metastasis process (CDH1, CDH13, ADAMTS1 and ADAMTS5), tumor suppression (LATS-1 and PTEN), WNT pathway (DKK-3, WIF-1, sFRP-1, sFRP-2, sFRP-4 and sFRP-5), JAK-STAT pathway (PTPN6 (SHP-1)), p53 pathway (p14, p73 and PPP1R13B (ASPP-1)), ubiquitination (PARK-2) and tyrosine kinase (SYK). Most of the T-ALL patients (44/50 cases) showed hypermethylation in at least one of these analyzed genes, particularly genes such as NES-1, ADAMTS5, WIF- 1 and sFRP-1 (Additional file 1) [9]. Patients were classified into two distinct groups according to the existence of CpG island methylator phenotype (CIMP): CIMP-positive, with three or more hypermethylated genes, and CIMP-negative, with two or less hypermethylated genes. Clinically, CIMP-positive patients presented significantly shorter disease-free survival (DFS) and overall survival (OS) than those of CIMP-negative counterparts.

A genome-wide study was performed on 19 ETV6-RUNX1-positive pediatric precursor B-ALL patients and revealed a unique DNA hypermethylation signature at diagnosis compared to remission. Associated genes were mostly implicated in cell fate commitment, gene regulation, and DNA binding where DNA methylation may have impaired gene function through transcriptional regulation. Interestingly, 15 hypermethylated genes were recurrent in B-ALL patients irrespective of the cytogenetic subtypes, including genes involved in cell cycle arrest (MYOD1 and BTG4), cell development (FOXE3, TCF3, PAX5 and RAG1), differentiation (PTPRZ1, PPARG and IKZF1) and WNT pathway (sFRP-1) [10].

Moreover, analysis of CpG methylation not only allowed T-ALL and B-ALL classification, but also distinguished subtypes among B-ALL patients. Methylation status of 416 methylation-involved or ALL-related genes was determined by methylation array in 401 patients with ALL [11]. Many of these genes were involved in key cellular functions like cell adhesion, apoptosis, proliferation and growth. Precursor B-ALL patients showed remarkably lower median methylation level than T-ALL patients. Methylation patterns clearly separated patients from the main cytogenetic subtypes of precursor B-ALL, such as high hyperdiploidy, t(12;21), 11q23, and t(1;19). Hypermethylation of COBL, CPVL, EVC, LRP1B, PAX8, PCDHGA12 and SPON2 were correlated with favorable prognosis.

Methylation status may also influence response to treatment in ALL. In a cohort study of initial diagnosed and relapsed matched B-ALL patients, genomic methylation level was distinctly higher in relapse than at newly diagnosis. A total of 905 genes were preferentially hypermethylated and 79 genes were hypomethylated. Integration analysis of methylation with gene expression profile and copy number abnormalities revealed six genes closely related to disease relapse. Among them, four genes (CDKN2A, COL6A2, PTPRO and CSMD1) were hypermethylated, down-regulated and focally deleted, and two genes (NOTCH4 and TOP1MT) were hypomethylated, up-regulated and focally amplified [12]. Of these genes, CDKN2A is an important tumor suppressor which controls cell cycle by stabilizing p53. PTPRO encodes a receptor-type protein tyrosine phosphatase, which inhibits cell proliferation and induces apoptosis.

Chronic lymphocytic leukemia (CLL)

Chronic lymphocytic leukemia (CLL) is an indolent disease with clonal expansion of mature neoplastic B cells. Somatic mutation status of the immunoglobulin heavy-chain variable (IGHV) gene is an indicator of favorable prognosis [13].

Genome-wide methylation analysis was performed in 10 CLL patients. An average of 4.8% of CpGs analyzed was aberrantly methylated compared with normal neutrophils. One-hundred-and-seventy-three genes were differentially methylated [14]. This study identified a hypermethylated gene, GRM7, which inhibited cAMP and induced cell apoptosis. Another methylation array covering 14495 genes was performed in 23 CLL cases. Significant difference in methylation pattern was observed between IGHV-unmutated and IGHV-mutated CLL subgroups, with 64 genes differentially methylated. Hypermethylated tumor suppressor genes (ABI3, SCGB2A1, VHL, GPX3, IGSF4 and SERPIND5) were identified in unmutated CLL. In mutated cases, hypermethylation genes were involved in cell proliferation and NF-κB pathway (ADORA3, AIRE, CARD15, LOC340061, UNC5CL and LDOC1) and MAPK pathway (PRF1, FABP7) [15].

Methylation profiling is also indicative in CLL prognosis prediction. Genome-wide analysis of methylated CpG amplification, coupled with promoter microarray, identified 22 of 280 aberrantly methylated genes in 78 CLL patients, compared to normal B cells from 10 healthy volunteers. These genes were enriched in cellular functions, including cell growth and differentiation, tissue and organ development, tissue morphology, cancer, cell death and cell cycle regulation [16]. Twenty-seven genes were mapped to the neighboring genetic region of TP53 in chromosome 17. Among these genes, PRIMA1, TFAP4, SIRT2 and TP53INP2 were previously reported to functionally interact with p53. Bisulfite pyrosequencing further confirmed hypermethylation status of 19 candidate genes (SOX11, DLX1, FAM62C, SOX14, RSPO1, ADCY5, HAND2, SPOCK, ING1, PRIMA1, BCL11B, LTBP2, NR2F2, GALGT2, LHX1, DLX4, KLK10, TFAP2 and APP). Survival analysis showed that LINE, APP, SALL1 and PRIMA1 were correlated with shorter OS.

Malignant lymphoma

Malignant lymphoma mainly includes non-Hodgkin’s lymphoma (NHL) and Hodgkin’s lymphoma (HL). Its incidence is increasing and now ranges among the tenth most frequent cancers worldwide.

Diffuse large B-cell lymphoma (DLBCL)

Diffuse large B-cell lymphoma (DLBCL) is one of the most common NHL. Two biologically distinct subtypes are identified by gene expression profiling: germinal center B-cell-like (GCB) DLBCL and activated B-cell-like (ABC) DLBCL [17].

Genome-wide methylation was analyzed in 24 GCB-DLBCL and 21 ABC-DLBCL patients. The CpGs of 12 genes showed a hypermethylation pattern in both DLBCL subtypes, including genes involved in cell cycle arrest (CDKN1C and MYOD1), apoptosis (GDNF), Rho pathway (DLC1), transcription factors (AR, GATA4, NEUROD1, ONECUT2 and TFAP2A), receptor proteins (DRD2 and GRIN2B) and metabolism process (MTHFR). Methylation status of genes FLJ21062 (C7orf63), ONECUT2 and GNMT differed between GCB-DLBCL and ABC-DLBCL. In addition, FLJ21062, BNIP3, MGMT, RBP1, GATA4, IGSF4 and CRABP1 showed significantly increased levels of DNA methylation with decreased gene expression [18].

Another study measured gene methylation status in 69 DLBCL patients treated with Rituximab combined with CHOP regimen (cyclophosphamide, hydroxydaunorubicin, vincristine, and prednisone). Supervised analysis identified 263 differentially methylated genes between GCB-DLBCL and ABC-DLBCL subtypes. These genes were mostly enriched in antigen processing-presentation pathway, cytokine and inflammatory pathway. Integrated data with expression profile further confirmed 16 genes (LANCL1, KCNK12, SORL1, CXorf57, SOX9, KIAA0746, ASPHD2, ARHGAP17, IKZF1, PMM2, IL12A, JDP2, PAK1, GALNS, FGD2 and LYAR) that distinguished these two subtypes with 92%-98% accuracy [19]. Some of these genes were previously recognized in signaling pathways, such as JAK-STAT (IL12A) and Rho pathway (ARHGAP17, PAK1 and FDG2).

Mantle cell lymphoma (MCL)

Mantle cell lymphoma (MCL) is an aggressive B-NHL that arises from naïve B cells in the mantle zone of the lymph nodes. It is characterized by t(11;14)(q13;q32) translocation and subsequent overexpression of CCND1.

Methylation study in MCL cell lines found 331 differentially expressed genes mapped to autosomal chromosomes. Pathway analysis revealed that top cellular functions represented cell death, cell cycle, cellular growth and proliferation. MassARRAY assay of 25 candidate genes in seven MCL cell lines and normal B cells showed 20 genes hypermethylated in more than one MCL cell line, encompassing cell differentiation (SOX9), cell adhesion (CDH1), cell cycle (GOS2) and apoptosis (LGALS3), p53 pathway (CDC14B) and PI3K pathway (THEM4), transcription factors (AHR, HOXA9, NR2F2, FOXC1, TWIST1) and others with unknown functions (ROBO1, NPTX2, CYB1B1, GPX3, MAL, PAX6, PTPRG1, TFPI2). Among them, seven genes, whose methylation was reported in different tumor models, appeared to be frequently methylated in primary cells of 38 MCL patients (SOX9, HOXA9, AHR, NR2F2, ROBO1, NPTX2 and CDH1). MCL patients with two or more methylated genes had higher proliferation index Ki-67, increased number of chromosomal abnormalities and shorter OS than those with none or only one methylated gene. Methylation of tumor suppressor genes SOX9 and HOXA9 were also associated with the above-mentioned clinicopathological parameters and poor disease outcome in MCL [20].

Another genome-wide methylation analysis was performed in primary MCL samples and found significant aberrations in promoter methylation pattern compared with normal B cells. DNA methylation was quantified for over 14000 gene promoter regions. Integration of methylation and expression profiling data revealed 4 hypermethylated genes (CDKN2B, HOXD8, MLF-1 and PCDH8) and 4 hypomethylated genes (CD37, HDAC1, NOTCH1 and CDK5). Among these genes, CDKN2B and CDK5 are involved in cell cycle control. HDAC1 and NOTCH1 are known targets for treating lymphoid malignancies. HOXD8, MLF-1 and PCDH8 are implicated in multiple tumor types. CD37 belongs to tetraspanin transmembrane family and is expressed mainly in B cells [21].

Hodgkin’s lymphoma (HL)

Screening of methylated genes was performed in HL KM-H2 cell line by microarray analysis before and after treatment with 5-aza-2’-deoxycitidine. Thirty tumor suppressive genes were identified, including genes in cellular adhesion (CADM1 (IGSF4), CD44 and THBS1), growth arrest (GADD45), p53 pathway (ZMAT3) and two transcription factors (IRF7 and KLF6). Among them, CADM1 was further confirmed methylated and down-regulated in primary HL cells. Restoration of CADM1 expression in HL cells decreased cell survival and increased their sensitivity to apoptosis, demonstrating that IGSF4 silencing by CpG methylation inhibited apoptosis in Reed-Sternberg cells, which was an important process in HL pathogenesis [22].

Another genome-wide methylation study of 13088 genes compared five HL cell lines (L-1236, L-428, KM-H2, HDLM-2 and U-HO1) to normal B cells and 20 germinal center derived B-cell lymphoma (gcdBCL). HL and gcdBCL showed 329 commonly hypermethylated genes, mainly involved in development and morphogenesis, WNT pathway and regulation of adenylated cyclase activity. Two-hundred-and-nine genes were distinctly hypermethylated in HL cell lines, compared to gcdBCL or normal B cells. Gene Ontology analysis indicated that genes were enriched for positive regulation of B-cell activation and T-cell differentiation, suggesting that hypermethylated genes in HL targeted the B-cell program [23].

PART II: Signaling pathways involved in alterations of methylation status

Epigenetic profiling showed different genomic DNA methylation patterns among diseases. Several signaling pathways, such as WNT pathway, JAK-STAT pathway and p53 pathway, are recurrently involved in lymphoid malignancies (Figure 1).
Figure 1

Key signaling pathways involved in genetic methylation of lymphoid malignancies. In WNT pathway, WNT binds to Frizzled and LRP to phosphorylate Dvl and downstream degrades complex containing APC, AXIN, CK1α, PPP2R4 and GSK-3β. β-catenin is then released and translocated into the nucleus, activating target gene expression. In JAK-STAT pathway, cytokines bind to transmembrane receptors and activate JAKs, who then activate transcription factors STATs. STATs then translocate into the nucleus and initiate target gene transcription. P53 is an important tumor suppressor, and functions through both transcription dependent and independent ways. MDM2 is the main negative regulator of p53. In lymphoid malignancies, important negative regulatory genes (indicated in yellow) are found hypermethylated and down-regulated, resulting in aberrantly activated signaling in tumor cells. Targeted therapies for specific WNT and JAK-STAT signaling pathways under preclinical and clinical evaluations are listed.

WNT pathway

WNT pathway is essential in hematopoiesis and plays an important role in controlling cell proliferation, differentiation and survival [24]. WNT encodes a family of secreted cysteine-rich glycoproteins. The ligand receptor of WNT contains transmembrane protein Frizzled and LPR5/6. The main downstream target of WNT pathway is β-catenin. In the absence of WNT binding to its receptor, β-catenin is stabilized and bound to E-cadherin. The excess β-catenin protein is phosphorylated and degraded by destruction complex containing APC, AXIN, CK1α, PPP2R4 and GSK-3β. Upon activation, the WNT ligand binds to its membrane receptors and cytoplasmic protein Dvl is accordingly recruited and activated by phosphorylation. Activated Dvl induces dissociation and subsequent inhibition of GSK-3β from the complex. β-catenin is then released and translocated into the nucleus, where it up-regulates target gene expression. There are also several antagonist proteins of WNT-Frizzled interaction, including DKK, WIF and sFRP family members.

Increasing evidence showed dysregulation of WNT signaling in lymphoid malignancies. Pediatric precursor B-ALLs present hypermethylation of WNT inhibitors (WIF-1, PTPRO, sFRP2, sFRP4, sFRP5, FZD10, DKK2 and DKK3), β-catenin/TCF/LEF complex inhibitors (APC and WT1), cadherin genes (CDH1, CDH11 and CD13) and SOX genes (SOX2, SOX3, SOX8, SOX9, SOX14 and SOX21). Moreover, in Ph-positive ALLs, the silencing of sFRP1, sFRP2, sFRP4, sFRP5, WIF1, DKK3, HDPR1 and WNT5A by methylation predicts longer DFS and OS [25]. Primary CLL samples show hypermethylation pattern of sFRP gene family, especially sFRP1 and sFRP4, [26]. Other WNT inhibitors, such as WIF1 and DKK3, are also methylated in CLL [27].

JAK-STAT pathway

JAK-STAT pathway plays an essential role in the transduction of extracellular cytokine signals into intracellular process during hematopoietic ontogeny. The JAK family contains four cytoplasmic tyrosine kinases (JAK1-3 and TYK2) which are activated after cytokine receptor activation. Downstream of JAKs activation is phosphorylation of STATs transcription factor family (STAT1-4, STAT5A, STAT5B and STAT6). The phosphorylated STATs form homo- or heterodimers and translocate into the nucleus, initiating target gene transcription [28]. Constitutive STAT activation leads to increased cell proliferation, tumorigenesis and decreased apoptosis.

SHP1 is an important tumor suppressor gene which blocks the JAK-STAT pathway by dephosphorylating the receptors and receptor-associated kinases. Frequent methylation of SHP1 was observed in MCL, as compared to normal B cells [29]. In another study, SHP1 methylation was observed in 100% NHL and 94% leukemia patients, with mRNA expression accordingly decreased [30]. This study also found recurrent methylation of SOCS1 gene, inhibitor of the JAK-STAT pathway through blocking JAK activation, in about 30% of NHL and leukemia patients.

P53 pathway

TP53 is one of the most frequently altered tumor suppressor genes in cancer. The encoded p53 protein, which is ubiquitously expressed in tissue, keeps genome stability under stress, and is involved in multiple cellular activities such as development, differentiation, aging and disease [31]. In normal state, p53 is inhibited and degraded by MDM2. When activated, p53 exerts its function through transcription-dependent and -independent activities.

Methylation in promoter CpG or in CCWGG motif of TP53 was observed in 32% of ALL patients and correlated with decreased mRNA expression [32]. In CLL and DLBCL cases, methylation of TP53 was also observed, but with less methylation rate (18.5% and 3.7%, respectively) [33, 34]. A recent study analyzed 24 genes involved in the p53 pathway in six ALL cell lines and found 13 genes to be aberrantly hypermethylated. These genes are involved in the regulation of p53-dependent apoptosis (DBC1, POU4F2, AMID, APAF1, ASPP1, TP73, NOXA, has-miR-34b and has-miR-34c,), cell cycle regulation (POU4F1 and CDKN1C) and regulation of p53 itself (LATS2 and DAPK1). Further confirmation analysis on independent cohort of 200 ALL cases showed that 78% of them present methylation in at least one of these 13 genes. These patients are characterized by lower complete remission (CR) rate (84% versus 91% in non-methylated group), higher relapse rate (46% versus 21%) and higher mortality rate (56% versus 19%). Survival analysis further indicated that hypermethylation of these genes is an independent prognostic factor both for DFS and OS [35].

PART III: Targeted therapy on genetic methylation and involved signaling pathways

Different from genetic abnormalities, epigenetic aberrations are possibly reversible. Great efforts have been made on the development of epigenetic modulators, mainly focusing on the inhibition of DNA methyltransferase (DNMT) and histone deacetylase (HDAC). Also, specific targeted therapies on involved signaling pathways are under active preclinical investigation.

DNMT inhibitors

DNMT inhibitors are small molecules that effectively inhibit DNA methylation. 5’-azacytidine (Azacytidine, Vidaza) and 5-aza-2’-deoxycitidine (Decitabine, Dacogen) have been approved by Food and Drug Administration (FDA) for treating hematological malignancies [36].

Successful treatment with 5’-azacytidine was first reported in a 74-year-old female patient with myelodysplastic syndrome transformed pre-B ALL. At the time of transformation, bone marrow examination demonstrated pre-B blasts with del(20)(q11.2). The patient received 5’-azacytidine monotherapy (75mg/m2 subcutaneously, for 7 consecutive days every 28 days, 6 cycles) and attained CR for over 6 months [37]. Induction of 5-aza-2’-deoxycitidine in childhood refractory ALL was also reported [38]. A four-year-old girl with relapsed B-ALL from hematopoietic stem cell transplantation (HSCT) received 5-aza-2’-deoxycitidine (15mg/m2 i.v., three times a day for 3 days) combined with dexamethasone. The patient achieved CR and received a second allogeneic HSCT.

A Phase II trial of 5’-azacytidine was carried out in nine patients with recurrent fludarabine-refractory CLL. All cases received 1 to 6 cycles of 5’-azacytidine (75 mg/m2 subcutaneously, for 7 consecutive days every 3 to 8 weeks). Although this trial was discontinued because of lack of response and treatment tolerance, one patient responded to treatment after four cycles with clinical improvement and was alive at last follow-up [39]. Another Phase I trial of 5-aza-2’-deoxycitidine in 16 relapsed/refractory CLL and four NHL patients aimed to determine the minimum effective dose of 5-aza-2’-deoxycitidine. Three different escalating dose schedules were examined. All patients tolerated well the first dose group (10 mg/m2/day for 10 days). In the other two dose groups (15 mg/m2/day for 10 days or 15 mg/m2/day for 5 days), dose-limiting toxicity occurred in 67% (4 out of 6 patients) and 50% (4 out of 8 patients) patients, respectively. Main adverse effects consisted of grade 3 to 4 neutropenia, thrombocytopenia and hyperbilirubinemia. Among twenty patients treated, eight had stable disease (SD) [40]. In vitro, 5’-azacytidine also showed cytotoxic activity in primary samples of high-risk (11q-/17p-) and low-risk (13q-) CLL [41].

HDAC inhibitors

HDAC inhibitors can open chromatin status and suppress histone deacetylase, thus inducing transcriptional reactivation of silenced genes. Major HDAC inhibitors approved by FDA include Romidepsin (Depsipeptide), Panobinostat and Suberoylanilide hydroxamic acid (SAHA, vorinostat).

Romidepsin was used in a Phase I clinical trial for treating 10 CLL patients. 13 mg/m2 Romidepsin was given intravenously on days 1, 8 and 15. No patient met the response criteria. However, seven had improved peripheral leukocyte counts and one had lymphadenopathy reduction [42]. Another Phase II study enrolled 25 patients with relapsed/refractory HL treated with 200 mg SAHA (twice daily 14 days every 3 weeks or 3 days per week). One patient achieved partial response (PR) and seven other patients had SD over 1 year [43]. Panobinostat was also effective in treating refractory HL. In a cohort of 129 HL patients relapse/refractory to HSCT, Panobinostat (40 mg 3 times per week) was well tolerated and achieved an overall response rate (ORR) of 27%, including 23% PR and 4% CR. Median PFS was 6.1 months and estimated 1-year OS rate was 78% [44].

In vitro, ALLs with MLL-rearrangement present particular hypomethylation pattern of proto-oncogenes, such as MYC, SET, RUNX1, RAN. HDAC inhibitors (Romidepsin, Panobinostat, SAHA, and Valproic acid) can reverse such unfavorable epigenetic pattern and effectively induce leukemic cell death [45]. Moreover, HDAC inhibitors synergistically interacted with 5-aza-2’-deoxycitidine in ALL, DLBCL and MCL cell lines [21, 46, 47].

Targeting WNT signaling pathway

Targeted therapies circumventing the WNT signaling pathway were in the preclinical stage. Their functions include inhibition of WNT-mediated transcription and inactivation of WNT target genes.

Non-steroid anti-inflammatory drugs (NSAIDs) inhibit the WNT signaling pathway through preventing β-catenin transcription complex formation. In T-cell leukemia Jurkat cell line, para-nitric oxide-donating acetylsalicylic acid (para-NO-ASA) induces β-catenin degradation, along with an increase of caspase-3 expression and induction of apoptosis [48]. Similar apoptosis-inducing effect is observed in primary CLL cells and in a xenograft murine model, while sparing normal hematopoiesis in vitro [49].

Quercetin is an inhibitor of β-catenin through GSK-3β inactivation [50]. In cell lines of T-ALL, DLBCL and MCL [51], quercetin inhibits WNT signaling and induces cell growth arrest and apoptosis. Importantly, CCND1, as well as anti-apoptotic BCL-XL and BCL-2, are significantly down-regulated after quercetin treatment [52].

Small molecule inhibitors of WNT cascade (CGP049090 and PKF115-584) were tested in CLL. These inhibitors efficiently induce CLL cell apoptosis, while normal B cells are not affected. Both agents suppressed tumor growth in a JVM-3 subcutaneous xenograft murine model [53].

Although not tested in lymphoid malignancies, several antibodies have been proved to inhibit proliferation and induce apoptosis in solid tumors, including antagonists of WNT [54, 55] and of WNT receptors [56, 57]. In addition, peptide mimetics are identified in modulating the WNT signaling. For example, the sFRP1-derived peptides inhibit colorectal cancer xenograft formation in mice [58].

Targeting JAK-STAT signaling pathway

Pacritinib (SB1518) is an inhibitor of JAK2. A Phase I trial on Pacritinib in 34 relapsed/refractory HL or NHL patients show well tolerance. Three PRs are observed at a dose of 300 mg/day. Fifteen patients achieved SD, 13 of which had 4%-46% tumor reductions. Most common adverse events are gastrointestinal toxicities [59].

Ruxolitinib is a JAK1/JAK2 inhibitor and a FDA approved drug for treatment of myeloproliferative neoplasm. Recently its anti-proliferative effect was reported in cell lines of HL and primary mediastinal B-cell lymphoma. Expression of anti-apoptotic gene BCL-XL and MCL-1 decreased in a dose-dependent manner [60]. Also in vitro, Pacritinib induces cell apoptosis, cell cycle arrest and inhibits proliferation in lymphoid cell lines, including Jurkat and MOLT-4 [61]. Other JAK2 inhibitors include Tryphostin (AG-490) and Lestaurtinib. Tryphostin enhances the cytotoxicity effect of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in primary T-ALL cells and in Jurkat and SUPT1 T cell lines [62]. Lestaurtinib induces dose-dependent cell growth inhibition and apoptosis in five HL cell lines derived from refractory patients and primary cells obtained from four HL patients [63].

AUH-6-96 is firstly identified in Drosophila. In HL cell line L540, AUH-6-96 treatment abrogates the signaling pathway by reducing the level of JAK3 and STAT3 phosphorylation, thus down-regulating BCL-XL expression. Cell viability assay showed that this drug selectively induces apoptosis in the cancer cell line, while normal cells are not affected [64].

Conclusions

Genetic methylation plays an important role in tumor transformation and progression in lymphoid malignancies. Accumulating data of DNA methylation study not only lead to disease classification and risk stratification, but also revealed multiple signaling pathways for targeted therapy development. Although preclinical and clinical investigations indicated their beneficial effects on patients, further study should be focused on the bio-therapeutic agents targeting the specific methylated genes and the methylation status of involved signaling pathways.

Abbreviations

ALL: 

Acute lymphoblastic leukemia

MS-PCR: 

Methylation specific-polymerase chain reaction

CIMP: 

CpG island methylator phenotype

DFS: 

Disease-free survival

OS: 

Overall survival

CLL: 

Chronic lymphocytic leukemia

IGHV: 

Immunoglobulin heavy-chain variable

NHL: 

Non-Hodgkin’s lymphoma

HL: 

Hodgkin’s lymphoma

DLBCL: 

Diffuse large B-cell lymphoma

GCB: 

Germinal center B-cell-like

ABC: 

Activated B-cell-like

MCL: 

Mantle cell lymphoma

gcdBCL: 

Germinal center derived B-cell lymphoma

CR: 

Complete remission

DNMT: 

DNA methyltransferase

HDAC: 

Histone deacetylase

FDA: 

Food and Drug Administration

HSCT: 

Hematopoietic stem cell transplantation

SD: 

Stable disease

PR: 

Partial response

ORR: 

Overall response rate

NSAIDs: 

Non-steroid anti-inflammatory drugs

para-NO-ASA: 

Para-nitric oxide-donating acetylsalicylic acid

TRAIL: 

Tumor necrosis factor-related apoptosis-inducing ligand.

Declarations

Acknowledgements

This work was supported, in part, by the National Natural Science Foundation of China (81172254 and 81101793), the Shanghai Commission of Science and Technology (11JC1407300), the Program of Shanghai Subject Chief Scientist (13XD1402700), and the “Shu Guang” project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation (09SG21).

Authors’ Affiliations

(1)
State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Shanghai Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine
(2)
Pôle de Recherches Sino-Français en Science du Vivant et Génomique, Laboratory of Molecular Pathology

References

  1. Chen W, Cooper TK, Zahnow CA, Overholtzer M, Zhao Z, Ladanyi M, Karp JE, Gokgoz N, Wunder JS, Andrulis IL, Levine AJ, Mankowski JL, Baylin SB: Epigenetic and genetic loss of Hic1 function accentuates the role of p53 in tumorigenesis. Cancer Cell 2004,6(4):387–398. 10.1016/j.ccr.2004.08.030PubMedView ArticleGoogle Scholar
  2. Hoffmann MJ, Schulz WA: Causes and consequences of DNA hypomethylation in human cancer. Biochem Cell Biol 2005,83(3):296–321. 10.1139/o05-036PubMedView ArticleGoogle Scholar
  3. Hutter G, Scheubner M, Zimmermann Y, Kalla J, Katzenberger T, Hubler K, Roth S, Hiddemann W, Ott G, Dreyling M: Differential effect of epigenetic alterations and genomic deletions of CDK inhibitors [p16(INK4a), p15(INK4b), p14(ARF)] in mantle cell lymphoma. Genes Chromosomes Cancer 2006,45(2):203–210. 10.1002/gcc.20277PubMedView ArticleGoogle Scholar
  4. Drexler HG: Review of alterations of the cyclin-dependent kinase inhibitor INK4 family genes p15, p16, p18 and p19 in human leukemia-lymphoma cells. Leukemia 1998,12(6):845–859. 10.1038/sj.leu.2401043PubMedView ArticleGoogle Scholar
  5. Hagiwara K, Li Y, Kinoshita T, Kunishma S, Ohashi H, Hotta T, Nagai H: Aberrant DNA methylation of the p57KIP2 gene is a sensitive biomarker for detecting minimal residual disease in diffuse large B cell lymphoma. Leuk Res 2010,34(1):50–54. 10.1016/j.leukres.2009.06.028PubMedView ArticleGoogle Scholar
  6. Corn PG, Kuerbitz SJ, van Noesel MM, Esteller M, Compitello N, Baylin SB, Herman JG: Transcriptional silencing of the p73 gene in acute lymphoblastic leukemia and Burkitt’s lymphoma is associated with 5’ CpG island methylation. Cancer Res 1999,59(14):3352–3356.PubMedGoogle Scholar
  7. Koyama M, Oka T, Ouchida M, Nakatani Y, Nishiuchi R, Yoshino T, Hayashi K, Akagi T, Seino Y: Activated proliferation of B-cell lymphomas/leukemias with the SHP1 gene silencing by aberrant CpG methylation. Lab Invest 2003,83(12):1849–1858. 10.1097/01.LAB.0000106503.65258.2BPubMedView ArticleGoogle Scholar
  8. Esteller M: Profiling aberrant DNA methylation in hematologic neoplasms: a view from the tip of the iceberg. Clin Immunol 2003,109(1):80–88. 10.1016/S1521-6616(03)00208-0PubMedView ArticleGoogle Scholar
  9. Roman-Gomez J, Jimenez-Velasco A, Agirre X, Prosper F, Heiniger A, Torres A: Lack of CpG island methylator phenotype defines a clinical subtype of T-cell acute lymphoblastic leukemia associated with good prognosis. J Clin Oncol 2005,23(28):7043–7049. 10.1200/JCO.2005.01.4944PubMedView ArticleGoogle Scholar
  10. Wong NC, Ashley D, Chatterton Z, Parkinson-Bates M, Ng HK, Halemba MS, Kowalczyk A, Bedo J, Wang Q, Bell K, Algar E, Craig JM, Saffery R: A distinct DNA methylation signature defines pediatric pre-B cell acute lymphoblastic leukemia. Epigenetics 2012,7(6):535–541. 10.4161/epi.20193PubMedView ArticleGoogle Scholar
  11. Milani L, Lundmark A, Kiialainen A, Nordlund J, Flaegstad T, Forestier E, Heyman M, Jonmundsson G, Kanerva J, Schmiegelow K, Soderhall S, Gustafsson MG, Lonnerholm G, Syvanen AC: DNA methylation for subtype classification and prediction of treatment outcome in patients with childhood acute lymphoblastic leukemia. Blood 2010,115(6):1214–1225. 10.1182/blood-2009-04-214668PubMedView ArticleGoogle Scholar
  12. Hogan LE, Meyer JA, Yang J, Wang J, Wong N, Yang W, Condos G, Hunger SP, Raetz E, Saffery R, Relling MV, Bhojwani D, Morrison DJ, Carroll WL: Integrated genomic analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic strategies. Blood 2011,118(19):5218–5226. 10.1182/blood-2011-04-345595PubMed CentralPubMedView ArticleGoogle Scholar
  13. Hamblin TJ, Davis Z, Gardiner A, Oscier DG, Stevenson FK: Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 1999,94(6):1848–1854.PubMedGoogle Scholar
  14. Rush LJ, Raval A, Funchain P, Johnson AJ, Smith L, Lucas DM, Bembea M, Liu TH, Heerema NA, Rassenti L, Liyanarachchi S, Davuluri R, Byrd JC, Plass C: Epigenetic profiling in chronic lymphocytic leukemia reveals novel methylation targets. Cancer Res 2004,64(7):2424–2433. 10.1158/0008-5472.CAN-03-2870PubMedView ArticleGoogle Scholar
  15. Kanduri M, Cahill N, Goransson H, Enstrom C, Ryan F, Isaksson A, Rosenquist R: Differential genome-wide array-based methylation profiles in prognostic subsets of chronic lymphocytic leukemia. Blood 2010,115(2):296–305. 10.1182/blood-2009-07-232868PubMedView ArticleGoogle Scholar
  16. Tong WG, Wierda WG, Lin E, Kuang SQ, Bekele BN, Estrov Z, Wei Y, Yang H, Keating MJ, Garcia-Manero G: Genome-wide DNA methylation profiling of chronic lymphocytic leukemia allows identification of epigenetically repressed molecular pathways with clinical impact. Epigenetics 2010,5(6):499–508. 10.4161/epi.5.6.12179PubMed CentralPubMedView ArticleGoogle Scholar
  17. Alizadeh AA, Eisen MB, Davis REMAC, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran TYUX, Powell JI, Yang L, Marti GE, Moore T, Hudson J jr, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO, et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000,403(6769):503–511. 10.1038/35000501PubMedView ArticleGoogle Scholar
  18. Pike BL, Greiner TC, Wang X, Weisenburger DD, Hsu YH, Renaud G, Wolfsberg TG, Kim M, Weisenberger DJ, Siegmund KD, Ye W, Groshen S, Mehrian-Shai R, Delabie J, Chan WC, Laird PW, Hacia JG: DNA methylation profiles in diffuse large B-cell lymphoma and their relationship to gene expression status. Leukemia 2008,22(5):1035–1043. 10.1038/leu.2008.18PubMed CentralPubMedView ArticleGoogle Scholar
  19. Shaknovich R, Geng H, Johnson NA, Tsikitas L, Cerchietti L, Greally JM, Gascoyne RD, Elemento O, Melnick A: DNA methylation signatures define molecular subtypes of diffuse large B-cell lymphoma. Blood 2010,116(20):e81-e89. 10.1182/blood-2010-05-285320PubMed CentralPubMedView ArticleGoogle Scholar
  20. Enjuanes A, Fernandez V, Hernandez L, Navarro A, Bea S, Pinyol M, Lopez-Guillermo A, Rosenwald A, Ott G, Campo E, Jares P: Identification of methylated genes associated with aggressive clinicopathological features in mantle cell lymphoma. PloS One 2011,6(5):e19736. 10.1371/journal.pone.0019736PubMed CentralPubMedView ArticleGoogle Scholar
  21. Leshchenko VV, Kuo PY, Shaknovich R, Yang DT, Gellen T, Petrich A, Yu Y, Remache Y, Weniger MA, Rafiq S, Suh KS, Goy A, Wilson W, Verma A, Braunschweig I, Muthusamy N, Kahl BS, Byrd JC, Wiestner A, Melnick A, Parekh S: Genomewide DNA methylation analysis reveals novel targets for drug development in mantle cell lymphoma. Blood 2010,116(7):1025–1034. 10.1182/blood-2009-12-257485PubMed CentralPubMedView ArticleGoogle Scholar
  22. Murray PG, Fan Y, Davies G, Ying J, Geng H, Ng KM, Li H, Gao Z, Wei W, Bose S, Anderton J, Kapatai G, Reynolds G, Ito A, Marafioti T, Woodman CB, Ambinder R, Tao Q: Epigenetic silencing of a proapoptotic cell adhesion molecule, the immunoglobulin superfamily member IGSF4, by promoter CpG methylation protects Hodgkin lymphoma cells from apoptosis. Am J Pathol 2010,177(3):1480–1490. 10.2353/ajpath.2010.100052PubMed CentralPubMedView ArticleGoogle Scholar
  23. Ammerpohl O, Haake A, Pellissery S, Giefing M, Richter J, Balint B, Kulis M, Le J, Bibikova M, Drexler HG, Seifert M, Shaknovic R, Korn B, Kuppers R, Martin-Subero JI, Siebert R: Array-based DNA methylation analysis in classical Hodgkin lymphoma reveals new insights into the mechanisms underlying silencing of B cell-specific genes. Leukemia 2012,26(1):185–188. 10.1038/leu.2011.194PubMedView ArticleGoogle Scholar
  24. Clevers H, Nusse R: Wnt/beta-catenin signaling and disease. Cell 2012,149(6):1192–1205. 10.1016/j.cell.2012.05.012PubMedView ArticleGoogle Scholar
  25. Martin V, Agirre X, Jimenez-Velasco A, Jose-Eneriz ES, Cordeu L, Garate L, Vilas-Zornoza A, Castillejo JA, Heiniger A, Prosper F, Torres A, Roman-Gomez J: Methylation status of Wnt signaling pathway genes affects the clinical outcome of Philadelphia-positive acute lymphoblastic leukemia. Cancer Sci 2008,99(9):1865–1868. 10.1111/j.1349-7006.2008.00884.xPubMedView ArticleGoogle Scholar
  26. Liu TH, Raval A, Chen SS, Matkovic JJ, Byrd JC, Plass C: CpG island methylation and expression of the secreted frizzled-related protein gene family in chronic lymphocytic leukemia. Cancer Res 2006,66(2):653–658. 10.1158/0008-5472.CAN-05-3712PubMedView ArticleGoogle Scholar
  27. Chim CS, Pang R, Liang R: Epigenetic dysregulation of the Wnt signalling pathway in chronic lymphocytic leukaemia. J Clin Pathol 2008,61(11):1214–1219. 10.1136/jcp.2008.060152PubMedView ArticleGoogle Scholar
  28. Chen E, Staudt LM, Green AR: Janus kinase deregulation in leukemia and lymphoma. Immunity 2012,36(4):529–541. 10.1016/j.immuni.2012.03.017PubMedView ArticleGoogle Scholar
  29. Chim CS, Wong KY, Loong F, Srivastava G: SOCS1 and SHP1 hypermethylation in mantle cell lymphoma and follicular lymphoma: implications for epigenetic activation of the Jak/STAT pathway. Leukemia 2004,18(2):356–358. 10.1038/sj.leu.2403216PubMedView ArticleGoogle Scholar
  30. Reddy J, Shivapurkar N, Takahashi T, Parikh G, Stastny V, Echebiri C, Crumrine K, Zochbauer-Muller S, Drach J, Zheng Y, Feng Z, Kroft SH, McKenna RW, Gazdar AF: Differential methylation of genes that regulate cytokine signaling in lymphoid and hematopoietic tumors. Oncogene 2005,24(4):732–736. 10.1038/sj.onc.1208032PubMedView ArticleGoogle Scholar
  31. Xu-Monette ZY, Medeiros LJ, Li Y, Orlowski RZ, Andreeff M, Bueso-Ramos CE, Greiner TC, McDonnell TJ, Young KH: Dysfunction of the TP53 tumor suppressor gene in lymphoid malignancies. Blood 2012,119(16):3668–3683. 10.1182/blood-2011-11-366062PubMed CentralPubMedView ArticleGoogle Scholar
  32. Agirre X, Vizmanos JL, Calasanz MJ, Garcia-Delgado M, Larrayoz MJ, Novo FJ: Methylation of CpG dinucleotides and/or CCWGG motifs at the promoter of TP53 correlates with decreased gene expression in a subset of acute lymphoblastic leukemia patients. Oncogene 2003,22(7):1070–1072. 10.1038/sj.onc.1206236PubMedView ArticleGoogle Scholar
  33. Valganon M, Giraldo P, Agirre X, Larrayoz MJ, Rubio-Martinez A, Rubio-Felix D, Calasanz MJ, Odero MD: p53 Aberrations do not predict individual response to fludarabine in patients with B-cell chronic lymphocytic leukaemia in advanced stages Rai III/IV. British J Haematology 2005,129(1):53–59. 10.1111/j.1365-2141.2005.05405.xView ArticleGoogle Scholar
  34. Amara K, Trimeche M, Ziadi S, Laatiri A, Hachana M, Sriha B, Mokni M, Korbi S: Presence of simian virus 40 DNA sequences in diffuse large B-cell lymphomas in Tunisia correlates with aberrant promoter hypermethylation of multiple tumor suppressor genes. Int J Cancer 2007,121(12):2693–2702. 10.1002/ijc.23038PubMedView ArticleGoogle Scholar
  35. Vilas-Zornoza A, Agirre X, Martin-Palanco V, Martin-Subero JI, San Jose-Eneriz E, Garate L, Alvarez S, Miranda E, Rodriguez-Otero P, Rifon J, Torres A, Calasanz MJ, Cruz Cigudosa J, Roman-Gomez J, Prosper F: Frequent and simultaneous epigenetic inactivation of TP53 pathway genes in acute lymphoblastic leukemia. PloS One 2011,6(2):e17012. 10.1371/journal.pone.0017012PubMed CentralPubMedView ArticleGoogle Scholar
  36. Fenaux P, Mufti GJ, Hellstrom-Lindberg E, Santini V, Finelli C, Giagounidis A, Schoch R, Gattermann N, Sanz G, List A, Gore SD, Seymour JF, Bennett JM, Byrd J, Backstrom J, Zimmerman L, McKenzie D, Beach C, Silverman LR: Efficacy of azacitidine compared with that of conventional care regimens in the treatment of higher-risk myelodysplastic syndromes: a randomised, open-label, phase III study. Lancet Oncol 2009,10(3):223–232. 10.1016/S1470-2045(09)70003-8PubMed CentralPubMedView ArticleGoogle Scholar
  37. Paulson K, Kumar R, Ahsanuddin A, Seftel MD: Azacytidine as a novel agent in the treatment of acute lymphoblastic leukemia. Leuk Lymphoma 2011,52(1):134–136. 10.3109/10428194.2010.512965PubMedView ArticleGoogle Scholar
  38. Yanez L, Bermudez A, Richard C, Bureo E, Iriondo A: Successful induction therapy with decitabine in refractory childhood acute lymphoblastic leukemia. Leukemia 2009,23(7):1342–1343. 10.1038/leu.2009.58PubMedView ArticleGoogle Scholar
  39. Malik A, Shoukier M, Garcia-Manero G, Wierda W, Cortes J, Bickel S, Keating MJ, Estrov Z: Azacitidine in fludarabine-refractory chronic lymphocytic leukemia: a phase II study. Clin Lymphoma Myeloma Leuk 2013,13(3):292–295. 10.1016/j.clml.2012.11.009PubMedView ArticleGoogle Scholar
  40. Blum KA, Liu Z, Lucas DM, Chen P, Xie Z, Baiocchi R, Benson DM, Devine SM, Jones J, Andritsos L, Flynn J, Plass C, Marcucci G, Chan KK, Grever MR, Byrd JC: Phase I trial of low dose decitabine targeting DNA hypermethylation in patients with chronic lymphocytic leukaemia and non-Hodgkin lymphoma: dose-limiting myelosuppression without evidence of DNA hypomethylation. Br J Haematol 2010,150(2):189–195.PubMed CentralPubMedGoogle Scholar
  41. Norberg M, Lindhagen E, Kanduri M, Rickardson L, Sundstrom C, Stamatopoulos K, Rosenquist R, Aleskog A: Screening for cytotoxic compounds in poor-prognostic chronic lymphocytic leukemia. Anticancer Res 2012,32(8):3125–3136.PubMedGoogle Scholar
  42. Byrd JC, Marcucci G, Parthun MR, Xiao JJ, Klisovic RB, Moran M, Lin TS, Liu S, Sklenar AR, Davis ME, Lucas DM, Fischer B, Shank R, Tejaswi SL, Binkley P, Wright J, Chan KK, Grever MR: A phase 1 and pharmacodynamic study of depsipeptide (FK228) in chronic lymphocytic leukemia and acute myeloid leukemia. Blood 2005,105(3):959–967.PubMedView ArticleGoogle Scholar
  43. Kirschbaum MH, Goldman BH, Zain JM, Cook JR, Rimsza LM, Forman SJ, Fisher RI: A phase 2 study of vorinostat for treatment of relapsed or refractory Hodgkin lymphoma: Southwest Oncology Group Study S0517. Leuk Lymphoma 2012,53(2):259–262. 10.3109/10428194.2011.608448PubMed CentralPubMedView ArticleGoogle Scholar
  44. Younes A, Sureda A, Ben-Yehuda D, Zinzani PL, Ong TC, Prince HM, Harrison SJ, Kirschbaum M, Johnston P, Gallagher J, Le Corre C, Shen A, Engert A: Panobinostat in patients with relapsed/refractory Hodgkin’s lymphoma after autologous stem-cell transplantation: results of a phase II study. J Clin Oncol 2012,30(18):2197–2203. 10.1200/JCO.2011.38.1350PubMedView ArticleGoogle Scholar
  45. Stumpel DJ, Schneider P, Seslija L, Osaki H, Williams O, Pieters R, Stam RW: Connectivity mapping identifies HDAC inhibitors for the treatment of t(4;11)-positive infant acute lymphoblastic leukemia. Leukemia 2012,26(4):682–692. 10.1038/leu.2011.278PubMedView ArticleGoogle Scholar
  46. Bhatla T, Wang J, Morrison DJ, Raetz EA, Burke MJ, Brown P, Carroll WL: Epigenetic reprogramming reverses the relapse-specific gene expression signature and restores chemosensitivity in childhood B-lymphoblastic leukemia. Blood 2012,119(22):5201–5210. 10.1182/blood-2012-01-401687PubMed CentralPubMedView ArticleGoogle Scholar
  47. Kalac M, Scotto L, Marchi E, Amengual J, Seshan VE, Bhagat G, Ulahannan N, Leshchenko VV, Temkin AM, Parekh S, Tycko B, O’Connor OA: HDAC inhibitors and decitabine are highly synergistic and associated with unique gene-expression and epigenetic profiles in models of DLBCL. Blood 2011,118(20):5506–5516. 10.1182/blood-2011-02-336891PubMed CentralPubMedView ArticleGoogle Scholar
  48. Nath N, Labaze G, Rigas B, Kashfi K: NO-donating aspirin inhibits the growth of leukemic Jurkat cells and modulates beta-catenin expression. Biochem Biophys Res Commun 2005,326(1):93–99.PubMedView ArticleGoogle Scholar
  49. Razavi R, Gehrke I, Gandhirajan RK, Poll-Wolbeck SJ, Hallek M, Kreuzer KA: Nitric oxide-donating acetylsalicylic acid induces apoptosis in chronic lymphocytic leukemia cells and shows strong antitumor efficacy in vivo. Clin Cancer Res 2011,17(2):286–293. 10.1158/1078-0432.CCR-10-1030PubMedView ArticleGoogle Scholar
  50. Park CH, Chang JY, Hahm ER, Park S, Kim HK, Yang CH: Quercetin, a potent inhibitor against beta-catenin/Tcf signaling in SW480 colon cancer cells. Biochem Biophys Res Commun 2005,328(1):227–234. 10.1016/j.bbrc.2004.12.151PubMedView ArticleGoogle Scholar
  51. Gelebart P, Anand M, Armanious H, Peters AC, Dien Bard J, Amin HM, Lai R: Constitutive activation of the Wnt canonical pathway in mantle cell lymphoma. Blood 2008,112(13):5171–5179. 10.1182/blood-2008-02-139212PubMed CentralPubMedView ArticleGoogle Scholar
  52. Kawahara T, Kawaguchi-Ihara N, Okuhashi Y, Itoh M, Nara N, Tohda S: Cyclopamine and quercetin suppress the growth of leukemia and lymphoma cells. Anticancer Res 2009,29(11):4629–4632.PubMedGoogle Scholar
  53. Gandhirajan RK, Staib PA, Minke K, Gehrke I, Plickert G, Schlosser A, Schmitt EK, Hallek M, Kreuzer KA: Small molecule inhibitors of Wnt/beta-catenin/lef-1 signaling induces apoptosis in chronic lymphocytic leukemia cells in vitro and in vivo. Neoplasia 2010,12(4):326–335.PubMed CentralPubMedView ArticleGoogle Scholar
  54. He B, You L, Uematsu K, Xu Z, Lee AY, Matsangou M, McCormick F, Jablons DM: A monoclonal antibody against Wnt-1 induces apoptosis in human cancer cells. Neoplasia 2004,6(1):7–14.PubMed CentralPubMedView ArticleGoogle Scholar
  55. Mikami I, You L, He B, Xu Z, Batra S, Lee AY, Mazieres J, Reguart N, Uematsu K, Koizumi K, Jablons DM: Efficacy of Wnt-1 monoclonal antibody in sarcoma cells. BMC cancer 2005, 5: 53. 10.1186/1471-2407-5-53PubMed CentralPubMedView ArticleGoogle Scholar
  56. Pode-Shakked N, Harari-Steinberg O, Haberman-Ziv Y, Rom-Gross E, Bahar S, Omer D, Metsuyanim S, Buzhor E, Jacob-Hirsch J, Goldstein RS, Mark-Danieli M, Dekel B: Resistance or sensitivity of Wilms’ tumor to anti-FZD7 antibody highlights the Wnt pathway as a possible therapeutic target. Oncogene 2011,30(14):1664–1680. 10.1038/onc.2010.549PubMedView ArticleGoogle Scholar
  57. Ettenberg SA, Charlat O, Daley MP, Liu S, Vincent KJ, Stuart DD, Schuller AG, Yuan J, Ospina B, Green J, Yu Q, Walsh R, Li S, Schmitz R, Heine H, Bilic S, Ostrom L, Mosher R, Hartlepp KF, Zhu Z, Fawell S, Yao YM, Stover D, Finan PM, Porter JA, Sellers WR, Klagge IM, Cong F: Inhibition of tumorigenesis driven by different Wnt proteins requires blockade of distinct ligand-binding regions by LRP6 antibodies. Proc Natl Acad Sci U S A 2010,107(35):15473–15478. 10.1073/pnas.1007428107PubMed CentralPubMedView ArticleGoogle Scholar
  58. Lavergne E, Hendaoui I, Coulouarn C, Ribault C, Leseur J, Eliat PA, Mebarki S, Corlu A, Clement B, Musso O: Blocking Wnt signaling by SFRP-like molecules inhibits in vivo cell proliferation and tumor growth in cells carrying active beta-catenin. Oncogene 2011,30(4):423–433. 10.1038/onc.2010.432PubMed CentralPubMedView ArticleGoogle Scholar
  59. Younes A, Romaguera J, Fanale M, McLaughlin P, Hagemeister F, Copeland A, Neelapu S, Kwak L, Shah J, De Castro Faria S, Hart S, Wood J, Jayaraman R, Ethirajulu K, Zhu J: Phase I study of a novel oral janus kinase 2 inhibitor, SB1518, in patients with relapsed lymphoma: evidence of clinical and biologic activity in multiple lymphoma subtypes. J Clin Oncol 2012,30(33):4161–4167. 10.1200/JCO.2012.42.5223PubMedView ArticleGoogle Scholar
  60. Yin C, Lee S, Ayello J, van de Ven C, Pao J, Mulvey E, Cairo MS: JAK1/JAK2 Inhibitor, ruxolitinib inhibits cell proliferation and induces apoptosis in hodgkin lymphomas (HL) and primary mediastinal B-cell lymphomas (PMBL). ASH Annu Meet Abstr 2012,120(21):4886.Google Scholar
  61. Hart S, Goh KC, Novotny Diermayr V, Hu CY, Hentze H, Tan YC, Madan B, Amalini C, Loh YK, Ong LC, William AD, Lee A, Poulsen A, Jayaraman R, Ong KH, Ethirajulu K, Dymock BW, Wood JW: SB1518, a novel macrocyclic pyrimidine-based JAK2 inhibitor for the treatment of myeloid and lymphoid malignancies. Leukemia 2011,25(11):1751–1759. 10.1038/leu.2011.148PubMedView ArticleGoogle Scholar
  62. Lanuti P, Bertagnolo V, Pierdomenico L, Bascelli A, Santavenere E, Alinari L, Capitani S, Miscia S, Marchisio M: Enhancement of TRAIL cytotoxicity by AG-490 in human ALL cells is characterized by downregulation of cIAP-1 and cIAP-2 through inhibition of Jak2/Stat3. Cell res 2009,19(9):1079–1089. 10.1038/cr.2009.80PubMedView ArticleGoogle Scholar
  63. Diaz T, Navarro A, Ferrer G, Gel B, Gaya A, Artells R, Bellosillo B, Garcia-Garcia M, Serrano S, Martinez A, Monzo M: Lestaurtinib inhibition of the Jak/STAT signaling pathway in hodgkin lymphoma inhibits proliferation and induces apoptosis. PloS one 2011,6(4):e18856. 10.1371/journal.pone.0018856PubMed CentralPubMedView ArticleGoogle Scholar
  64. Kim BH, Yin CH, Guo Q, Bach EA, Lee H, Sandoval C, Jayabose S, Ulaczyk-Lesanko A, Hall DG, Baeg GH: A small-molecule compound identified through a cell-based screening inhibits JAK/STAT pathway signaling in human cancer cells. Mol Cancer Ther 2008,7(9):2672–2680. 10.1158/1535-7163.MCT-08-0309PubMed CentralPubMedView ArticleGoogle Scholar

Copyright

© Zhao et al.; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement